1. Field of the Invention
Embodiments of the present invention generally relate to a system and method for providing customer service in a contact center and particularly to a system and method for calculating estimated wait time for customers.
2. Description of Related Art
Contact centers are employed by many enterprises to service inbound and outbound contacts from customers. A typical contact center includes a switch and/or server to receive and route incoming packet-switched and/or circuit-switched contacts and one or more resources, such as human agents and automated resources (e.g., Interactive Voice Response (IVR) units), to service the incoming contacts. Contact centers distribute contacts, whether inbound or outbound, for servicing to any suitable resource according to predefined criteria. In many existing systems, the criteria for servicing the contact from the moment that the contact center becomes aware of the contact until the contact is connected to an agent are client or operator-specifiable (i.e., programmable by the operator of the contact center), via a capability called vectoring. Normally in present-day automatic call distributor (ACD) when the ACD system's controller detects that no agents are available for handling incoming contacts, the contacts are placed in queues to wait till an agent becomes available to service the incoming contacts. When an agent becomes available to handle the contact, the ACD system's controller identifies all predefined contact-handling queues for the agent (usually in some order of priority) and delivers to the agent the highest-priority, oldest contact that matches the agent's highest-priority queue.
For smooth and effective functioning of routing calls in the contact center is to estimate how long a contact has to wait in the queue before being serviced by an agent of the contact center. Existing solutions for calculating Estimated Wait Time (EWT) metrics in a contact center use simple counting algorithms, and/or generic averages to inform the estimates to the incoming contacts. The average values used are calculated across a whole contact center system, for a whole queue or for high-level groupings such as ‘new customer’, ‘support’ or ‘sales’. Further, unaccounted variations, such as complexity of contacts, associated with using generically averaged values lead to inaccurate estimations and unreliability in a real world system. Therefore, Estimated Wait Time can become increasingly inaccurate if other contacts being handled at the time of calculation take longer time to process than initially predicted by using the algorithms.
In addition to the varying complexity of contacts queued or in progress, the skills and efficacy of specific agents available at request time can have a dramatic effect on the accuracy of the calculated Estimated Wait Time. The agent(s) most suited to service an incoming contact may not be working on that day, and therefore the ‘average handling time’ value would be skewed as the existing solutions include these agents with the high efficacy and best handling times while calculating the estimated wait time for the incoming contacts.
Further, existing solutions use an agent desktop application to update an estimation of the estimated wait time based on the agent progress on the ongoing contact. The progress of the ongoing contacts is either updated manually by an agent or automatically through indicators (explained below). Therefore, this may lead to inaccurate estimates of the estimated wait time for the incoming contacts.
Further, existing solutions use averaging formulae by creating data points during the processing of each contact to improve the accuracy of estimated wait time predictions. Typical data points include such as when a contact enters or exits a queue, how fast a contact progresses through a queue, when an agent logs in or out or goes on break or returns from break, etc. In addition, an improved method to improve the accuracy of estimated wait time is proposed by creating additional data points during the processing of each incoming contact. The improved method makes use of indicators to inform the estimate of how much time the incoming contact will take to conclude. The indicators can be actuated either manually by an agent of the contact center, or automatically. The indicators may include ‘New customers’, ‘existing customers’, and ‘Wrap up’. However, these methods of calculating Estimated Wait Time are too simplistic, as they use generically averaged values to inform the estimate wait time for the customers.
There is thus a need for an improved customer support service system and method to provide most accurate estimate wait time for every contact currently queued or being handled by the system.